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At least 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Assessing the Impact of Lubrication on Efficiency and Life Cycle Economics of the US Wind Turbine Fleet: Cooperative Research and Development (Final Report)

As with any mechanical system, lubrication plays a key role in the performance of wind turbines used to generate electricity. The lubricant design offers a way to optimize the competing requirements of efficiency, component reliability, and maintenance strategy. This project will estimate the impact of improved lubrication on the levelized cost of energy of the US wind turbine fleet as a means of identifying opportunities for disruptive innovation or system-level optimization. The models developed will provide a clear understanding of the benefits and potential for advanced lubrication of wind turbines. The project will enable identification of high value targets for wind turbine component suppliers and a roadmap that highlights where the greatest return on technology investment can be achieved. This will promote efficient resource allocation in areas of new technology development.

17 WIND ENERGY↗
DOE OSTI2023

DQ Admittance Model Extraction for IBRs via Gaussian Pulse Excitation

While $dq$ admittance models have shown to be very useful for stability analysis, extracting admittance models of inverter-based resources (IBRs) from the electromagnetic transient (EMT) simulation environment using frequency scans takes time. In this letter, a new perturbation method based on Gaussian pulses in combination with the system identification algorithms shows great promise for parametric $dq$ admittance model extraction. We present the $dq$ admittance model extracting method for a type-4 wind turbine. Challenges in implementing Gaussian pulse excitation are also pointed out. In conclusion, the extracted $dq$ admittance model via the new method shows to have a high matching degree with the measurements obtained from frequency scans.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Wake steering of multirotor wind turbines

Abstract In this paper, wake steering is applied to multirotor turbines to determine whether it has the potential to reduce wind plant wake losses. Through application of rotor yaw to multirotor turbines, a new degree of freedom is introduced to wind farm control such that wakes can be expanded, channelled or redirected to improve inflow conditions for downstream turbines. Five different yaw configurations are investigated (including a baseline case) by employing large‐eddy simulations (LES) to generate a detailed representation of the velocity field downwind of a multirotor wind turbine. Two lower‐fidelity models from single‐rotor yaw studies (curled‐wake model and analytical Gaussian wake model) are extended to the multirotor case, and their results are compared with the LES data. For each model, the wake is analysed primarily by examining wake cross‐sections at different downwind distances. Further quantitative analysis is carried out through characterisations of wake centroids and widths over a range of streamwise locations and through a brief analysis of power production. Most significantly, it is shown that rotor yaw can have a considerable impact on both the distribution and magnitude of the wake velocity deficit, leading to power gains for downstream turbines. The lower‐fidelity models show small deviation from the LES results for specific configurations; however, both are able to reasonably capture the wake trends over a large streamwise range.

17 WIND ENERGY↗
DOE OSTI2023

OC6 project Phase III: validation of the aerodynamic loading on a wind turbine rotor undergoing large motion caused by a floating support structure

Abstract. This paper provides a summary of the work done within Phase III of the Offshore Code Comparison Collaboration, Continued, with Correlation and unCertainty (OC6) project, under the International Energy Agency Wind Technology Collaboration Programme Task 30. This phase focused on validating the aerodynamic loading on a wind turbine rotor undergoing large motion caused by a floating support structure. Numerical models of the Technical University of Denmark 10 MW reference wind turbine were validated using measurement data from a 1:75 scale test performed during the UNsteady Aerodynamics for FLOating Wind (UNAFLOW) project and a follow-on experimental campaign, both performed at the Politecnico di Milano wind tunnel. Validation of the models was performed by comparing the loads for steady (fixed platform) and unsteady (harmonic motion of the platform) wind conditions. For the unsteady wind conditions, the platform was forced to oscillate in the surge and pitch directions under several frequencies and amplitudes. These oscillations result in a wind variation that impacts the rotor loads (e.g., thrust and torque). For the conditions studied in these tests, the system aerodynamic response was almost steady. Only a small hysteresis in airfoil performance undergoing angle of attack variations in attached flow was observed. During the experiments, the rotor speed and blade pitch angle were held constant. However, in real wind turbine operating conditions, the surge and pitch variations would result in rotor speed variations and/or blade pitch actuations, depending on the wind turbine controller region that the system is operating. Additional simulations with these control parameters were conducted to verify the fidelity of different models. Participant results showed, in general, a good agreement with the experimental measurements and the need to account for dynamic inflow when there are changes in the flow conditions due to the rotor speed variations or blade pitch actuations in response to surge and pitch motion. Numerical models not accounting for dynamic inflow effects predicted rotor loads that were 9 % lower in amplitude during rotor speed variations and 18 % higher in amplitude during blade pitch actuations.

17 WIND ENERGY↗
DOE OSTI2024

Modeling the effect of wind speed and direction shear on utility‐scale wind turbine power production

Abstract Wind speed and direction variations across the rotor affect power production. As utility‐scale turbines extend higher into the atmospheric boundary layer (ABL) with larger rotor diameters and hub heights, they increasingly encounter more complex wind speed and direction variations. We assess three models for power production that account for wind speed and direction shear. Two are based on actuator disc representations, and the third is a blade element representation. We also evaluate the predictions from a standard power curve model that has no knowledge of wind shear. The predictions from each model, driven by wind profile measurements from a profiling LiDAR, are compared to concurrent power measurements from an adjacent utility‐scale wind turbine. In the field measurements of the utility‐scale turbine, discrete combinations of speed and direction shear induce changes in power production of −19% to +34% relative to the turbine power curve for a given hub height wind speed. Positive speed shear generally corresponds to over‐performance and increasing magnitudes of direction shear to greater under‐performance, relative to the power curve. Overall, the blade element model produces both higher correlation and lower error relative to the other models, but its quantitative accuracy depends on induction and controller sub‐models. To further assess the influence of complex, non‐monotonic wind profiles, we also drive the models with best‐fit power law wind speed profiles and linear wind direction profiles. These idealized inputs produce qualitative and quantitative differences in power predictions from each model, demonstrating that time‐varying, non‐monotonic wind shear affects wind power production.

Energy & Fuels↗
DOE OSTI2026

Leveraging generative artificial intelligence to bridge domain gaps in wind turbine research

A central challenge in wind turbine health monitoring is the scarcity of real-world data due to limited instrumentation, leading researchers to rely on simulation models that often suffer from reduced fidelity. However, even within simulation environments, discrepancies arise because of modeling assumptions, and configuration fidelities, creating domain gaps that limit the transferability of learned representations. Here, to investigate domain translation under controlled conditions, this project explores the use of generative artificial intelligence, specifically cycle-consistent generative adversarial networks (CGANs), to bridge the gap between OpenFAST simulation models representing 1.5 MW and 5 MW wind turbines. A physics-informed CGAN architecture is introduced, where a simplified turbine tower dynamics model is incorporated into the training loss to ensure physically consistent outputs. Quantitative results showed moderate to high agreement in frequency-domain features. Incorporating the physics-informed loss function improved the R 2 values by 30%, reduced the RMSE from 1.39 to 1.1 m/s 2 , and reduced training time by 82%. Furthermore, under increased turbulence intensity (IEC Category A), the RMSE remained stable at approximately 1.1 m/s 2 . While the present study is entirely simulation-based, it establishes a pipeline for evaluating physics-informed generative domain translation, which may serve as a foundation for future simulation-to-reality validation studies.

17 WIND ENERGY↗
DOE OSTI2023

On the Low Risk of Subsynchronous Resonance (SSR) in Type III Wind Turbines Operating in Grid-Forming Control

We have shown in a previous work that the risk of sub-synchronous resonance (SSR) between a wind power plant with Type III wind turbines and series-compensated transmission lines is low when the wind turbines in the plant are operated in grid-forming mode, instead of the standard grid-following mode. The fundamental mechanism behind the improved damping characteristics is explained in this paper by modeling the positive and negative sequence impedances of Type III wind turbines for GFM operation mode. It is discovered that the GFM control naturally acts against the negative resistance of Type III wind turbines that results from an interaction between the proportional gain of the rotor-side converter current controller and negative slip. The developed sequence impedance models and improved damping behavior are verified using PSCAD simulations of a 2.5-MW Type III GFM wind turbine. The modeling predictions are also supported by experimentally measuring the sequence impedance response of a 2.5-MW Type III wind turbine during operation in GFL and GFM modes.

grid-following turbine↗
DOE OSTI2023

Impact of Aerodynamic Modeling Assumptions on Flutter Speeds of Vertical-Axis Wind Turbines

Theodorsen’s unsteady aerodynamic theory has been used extensively in flutter speed prediction of wind turbine blades. In this study, three key assumptions of Theodorsen theory (thin airfoil, flat wake, and small angle of attack) have been revisited, and all three assumptions have been addressed in combination to obtain new lift and moment equations that are subsequently applied in flutter calculations for full-scale vertical-axis wind turbine (VAWT) rotors, not just of an individual airfoil or blade. Furthermore, edgewise aerodynamics terms are added to the lift and moment equations to include their effects on flutter speeds. The newly obtained equations were implemented in the OWENS (Offshore Wind ENergy Simulation) toolkit, which is an FEM (Finite Element Method)-based toolkit for aeroelastic analysis of VAWTs. The effect of modifying each of these assumptions has been studied for the flutter RPM prediction of three primary modes of flutter of VAWTs: propeller, butterfly, and tower modes. For the land-based case, the most change was observed for the flutter RPM of the propeller mode, with a maximum increase of 2.62% for the two-bladed UTD 5 MW VAWT case. For the floating offshore case, the primary flutter modes (tower and platform pitch) were not significantly affected.

Engineering↗
NASA NTRS1980

Numerical calculation of steady inviscid full potential compressible flow about wind turbine blades

An exact nonlinear mathematical model that accounts for three-dimensional cascade effects about the inner portions of the rotor blades and compressibility effects about the tip regions of the blades was derived. An artificially time dependent version was iteratively solved by a finite volume technique involving an artificial viscosity and a three-level consecutive mesh refinement. The exact boundary conditions were applied by generating a boundary conforming periodic computation mesh.

Dulikravich, D. S.↗
DOE OSTI2023

On the Low Risk of SSR in Type III Wind Turbines Operating with Grid-Forming Control

We have shown in previous work that the risk of subsynchronous resonance between wind power plants with Type III wind turbines and series-compensated transmission lines is low when the wind turbines are operated in grid-forming (GFM) mode instead of the standard grid-following mode. This paper explains the fundamental mechanism behind the improved damping characteristics by modeling the positive- and negative-sequence impedances of Type III wind turbines in GFM control mode. Here it is discovered that the GFM control naturally acts against the negative resistance behavior of Type III wind turbines at subsynchronous frequencies that results from an interaction between the rotor-side converter current controller and negative slip. The developed impedance models in the sequence domain and the improved damping behavior are verified using PSCAD simulations of a 2.5-MW Type III GFM wind turbine. The modeling predictions are also supported by experimentally measuring the impedance response of a 2.5-MW Type III wind turbine in GFM mode.

17 WIND ENERGY↗
DOE OSTI2023

Characterization of wind turbine flow through nacelle-mounted lidars: a review

This article provides a comprehensive review of the most recent advances in the planning, execution, and analysis of inflow and wake measurements from nacelle-mounted wind Doppler lidars. Lidars installed on top of wind turbines provide a holistic view of the inflow and wake characteristics required to characterize and optimize wind turbine performance, carry out model validation and calibration, and aid in real-time control. The need to balance the enhanced capabilities and limitations of lidars compared to traditional anemometers inspired a broad variety of approaches for scan design and wind reconstruction, which we discuss in this review. We give particular emphasis to identifying common guidelines and gaps in the available literature with the aim of providing an exhaustive picture of the state-of-the-art techniques for reconstructing wind plant flow using nacelle-mounted lidars.

17 WIND ENERGY↗
DOE OSTI2025

Main Shaft Bending Moment Analysis for a Gamesa G97 2-MW Wind Turbine

In a collaborative project between Siemens Gamesa Renewable Energy and the National Renewable Energy Laboratory (NREL), a cost-effective method to measure dynamic main shaft torque and the influence of non-torque loads was applied to the gearbox of the Gamesa G97 2-megawatt (MW) wind turbine at the NREL Flatirons Campus and verified through a field test campaign that took place in 2023. The method involved the installation of fiber-optic sensors on the ring gear of the gearbox. Additionally, traditional strain gauges and a rotary encoder were installed on the main shaft to measure mechanical torque and orthogonal bending moments. We compare the measured total main shaft bending moments from the field test campaign to those predicted by an updated OpenFAST model of the G97 wind turbine for similar environmental conditions. We also assessed the sensitivity of the predicted bending moment to varying levels of turbulence intensity, shear exponent, and yaw error.

17 WIND ENERGY↗
DOE OSTI2020

Resource and Load Compatibility Assessment of Wind Energy Offshore of Humboldt County, California

Floating offshore wind is being considered in northern California as indicated by the Bureau of Ocean Energy Management’s issuance of a lease consideration in the Humboldt Call Area. Humboldt County offers access to this enormous resource, but local electric load and transmission are limited. The potential impacts of offshore wind generators at three different scales were studied using a regional grid model of Humboldt County. Offshore wind generation was calculated using modeled wind speed data and 12-MW turbine specifications and integrated with projected load and historical generation. Offshore wind farms deployed in the Humboldt Call Area achieve annual capacity factors between 45% and 54% after losses and maintenance. Power output is variable between and within seasons, with full power output 30% of the time and no output approximately 20% of the time. Electricity from a 48-MW wind farm provides 22% of regional load with limited exports. A 144-MW wind farm serves 38% of local load, exporting 40% of its electricity with the extant 70-MW transmission capacity. A full build-out of 1836 MW would result in 88% curtailment with existing transmission. Across scenarios, offshore wind variability necessitates reliance on existing power plants to meet local demand in periods of low wind.

17 WIND ENERGY↗
NASA NTRS1978

Employing static excitation control and tie line reactance to stabilize wind turbine generators

An analytical representation of a wind turbine generator is presented which employs blade pitch angle feedback control. A mathematical model was formulated. With the functioning MOD-0 wind turbine serving as a practical case study, results of computer simulations of the model as applied to the problem of dynamic stability at rated load are also presented. The effect of the tower shadow was included in the input to the system. Different configurations of the drive train, and optimal values of the tie line reactance were used in the simulations. Computer results revealed that a static excitation control system coupled with optimal values of the tie line reactance would effectively reduce oscillations of the power output, without the use of a slip clutch.

Hwang, H. H.↗
DOE OSTI2020

Implementation of Substructure Flexibility and Member-Level Load Capabilities for Floating Offshore Wind Turbines in OpenFAST

OpenFAST is an open-source, physics-based engineering tool applicable to the load analysis of land-based and offshore wind turbines, including floating offshore wind turbines. The substructure for a floating wind turbine has historically been modeled in OpenFAST as a rigid body with hydrodynamic loads lumped at a point, which enabled the tool to predict the global response of the floating substructure but not the structural loads within its individual members. This limitation is an impediment to designing floating substructures - especially newer designs that are more streamlined, flexible, and cost-effective. This paper presents the development of new functionality in OpenFAST to model floating substructure flexibility and member-level loads, as well as the concepts and mathematical background needed to understand and apply it correctly.

17 WIND ENERGY↗
DOE OSTI2020

Multiscale Framework Simulates Utility-Scale Wind Plant in Its Natural Environment. First-ever simulation could lead to a vital understanding of wind plant performance

Wind plant performance depends on local environmental conditions—and understanding those conditions is crucial to research on wind plant dynamics. Factors such as sloping terrain, surface type and cover, atmospheric heating and cooling, and weather events all play a role in determining the winds that turbines convert into power. However, most models used for wind plant design and operation do not sufficiently account for environmental effects. This can limit our understanding of wind plant dynamics and, thus, our ability to design, site, and operate wind plants for maximum power production and reliability. To meet this challenge, Arthur and other LLNL researchers partnered with scientists at the National Center for Atmospheric Research; the University of California, Berkeley; the University of Colorado, Boulder; and Texas Tech University to develop and demonstrate a novel, mesoscale-tomicroscale wind plant modeling framework.

17 WIND ENERGY↗
DOE OSTI2021

Machine Learning for Gearbox Fault Prediction by Using Both Scada and Modeled Data

This presentation outlines the work in the paper titled "Prognostics of Wind Turbine Gearbox Bearing Failures Using SCADA and Modeled Data" published by the PHM Society and presented at its 2020 annual conference. It is accessible at https://papers.phmsociety.org/index.php/phmconf/article/download/1292/862. The technical work is on machine learning approaches for prognostics for gearbox faults. The methodology combines SCADA time series data and physics domain modeling data, derived from the models developed by the NREL team, as inputs to machine learning models to predict gearbox bearing failures with one month lead time. Based on SCADA data, modeled data, and bearing failure log data from an actual wind plant, the performances of different machine-learning models on unseen data are then evaluated using industry-standard metrics such as precision, recall, and F1 score, and AUC (area under receiver operating characteristic curve). Results show the overall system performance enhancement in predicting bearing failure when modeled data are included with SCADA data. The reduction in terms of false alarms is about 50%, and improvement in terms of precision, and F1 score, and AUC is about 33%, and 12%, and 6% respectively, based on the best modeling case in this study.

49 EE - Wind and Water Power Program - Wind (EE-4W↗